10.46243/jst.2023.v8.i12.pp61-77 registered
THE INTELLIGENCE AMBULANCE: BRIDGING AI AND HUMAN INTERACTION TECHNOLOGIES
Resolves to https://www.jst.org.in/index.php/pub/article/view/851
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2023.v8.i12.pp61-77
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JournalArticle — an article in a journal · Digital · Visual · en
THE INTELLIGENCE AMBULANCE: BRIDGING AI AND HUMAN INTERACTION TECHNOLOGIES (PrincipalTitle)
Published 2023-12-12
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 8 · issue 12 · pages 61–77
Agents
- S. Samreen S. Samreen (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2023.v8.i12.pp61-77
Abstract
Traditionally, ambulances have functioned as vehicles equipped with basic life support equipment, staffed by paramedics and emergency medical technicians. Their primary role has been to provide initial care during transportation to a medical facility. Communication with hospitals and the processing of patient information have been manual and time-consuming, lacking real-time data analysis capabilities and decision support tools that AI can offer in emergency situations. 1Assistant Professor,2UG Students, Department of Information Technology 1,2Malla Reddy Engineering College for Women, Maisammaguda, Dhulapally, Kompally, Secunderabad-500100, Telangana, India DOI:https://doi.org/10.46243/jst.2023.v8.i12.pp61 -7738 S. Samreen, B.Sai Sruthi, A.Manisha Kumari, B Vaishnavi: THE INTELLIGENCE AMBULANCE: BRIDGING AI AND HUMAN INTERACTION TECHNOLOGIES The challenge at hand involves optimizing emergency medical responses and care through the seamless integration of AI and human interaction technologies within ambulances. This optimization targets critical areas such as quick and accurate diagnosis, efficient communication between emergency responders and healthcare facilities, and the provision of real-time medical information to enhance decision-making during emergencies. The ultimate goal is to create a seamless, intelligent, and responsive system that significantly improves patient outcomes during critical moments. The need for an intelligent ambulance arises from the understanding that leveraging AI and human interaction technologies can markedly enhance the efficiency and effectiveness of emergency medical services. In critical situations, where quick and accurate decision-making is crucial, the integration of intelligent systems can provide invaluable support to healthcare professionals. This approach also addresses the improvement of communication, data sharing, and coordination between ambulances, hospitals, and other healthcare entities. The historical context underscores the limitations of traditional EMS systems and highlights the potential for innovation through the integration of AI, ushering in a new era of intelligent emergency medical services. The progression of emergency medical services (EMS) has witnessed substantial advancements, with a dedicated emphasis on refining response times, elevating patient care, and enhancing overall outcomes. A pivotal transformative approach in this trajectory involves the integration of artificial intelligence (AI) and human interaction technologies into ambulances, signifying a paradigm shift in the landscape of emergency medical care. Delving into the historical context, ambulances traditionally functioned as vehicles equipped with fundamental life support apparatus, manned by paramedics and emergency medical technicians. Their primary role centered around providing initial care during transportation to a medical facility. However, communication processes with hospitals and the manual processing of patient information were notably time-consuming. The conventional system also lacked real-time data analysis capabilities and decision support tools, aspects where AI demonstrates significant potential in emergency scenarios. The prevailing challenge revolves around optimizing emergency medical responses and care by seamlessly integrating AI and human interaction technologies within ambulances. This optimization necessitates addressing complex issues, including the imperative for swift and accurate diagnosis, fostering effective communication between emergency responders and healthcare facilities, and ensuring the realtime provision of medical information to enhance decision-making processes. LITERATURE SURVEY In 2020 Akca et al. [1] put forward a paper which mainly emphasizes on “Intelligent Ambulance Management System in Smart Cities.” technique to manage ambulance and emergency services. This research is efficient to cover all the things needed to Design & Development of Intelligent Ambulance Concept – AI and Human Interface Technology Section A-Research paper 179 Eur. Chem. Bull. 2023,12(Special Issue 9), 177-188 develop a smart ambulance management framework but lacks to explain how the system can work in real time with a combination of mobile computing, cloud computing and standalone application together. In 2021 Ganesh et al. [2] presented a study on “health machine to handle covid-19 related health emergencies” technique to manage ambulance and emergency services. This research effectively covers all the requirements for developing a smart ambulance management framework, but it falls short on describing how the system may function in real time by combining mobile, cloud, and standalone applications altogether. Gargi Beri, Ashwin Channawar, Pankaj Ganjare, Amruta Gate, Prof. Vijay Gaikwad published, “Intelligent Ambulance with Traffic Control” [3]. This study includes a traff
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2023.v8.i12.pp61-77 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | THE INTELLIGENCE AMBULANCE: BRIDGING AI AND HUMAN INTERACTION TECHNOLOGIES (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: S. Samreen S. Samreen publisher: Longman Publishers published: 2023-12-12 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 12 · pp. 61–77 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2024-02-16 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
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History — the ledger
Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 102 fields set · sha256 27f3519245f7… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | abstract.value: container.titles.0.value: |
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